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Agent based heterogeneous data integration and maintenance decision support for high-speed railway signal system

机译:基于代理的高速铁路信号系统异构数据集成和维护决策支持

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In this paper, we propose a novel framework of integration of multi-source heterogeneous data and intelligent maintenance decision support for High-speed Railway Signal System. The framework uses the multi-agent system to deal with the multi-source data. Each agent has its own task varying from transferring RDB (Rational Database) data to RDF (Resource Description Framework) file, and then fusing local RDF to global RDF by Apache Jena API and D2RQ. In addition, a CBR (Case-Based Reasoning) based intelligent maintenance decision support for the fault diagnosis has been constructed by combing the rough set with the Euclidean distance. The correctness and efficiency of the proposed framework has been verified by maintenance data derived from VOBE (Vehicle Equipment On Board) of CTCS-300T operating on Wuhan-Guangzhou Line.
机译:在本文中,我们为高速铁路信号系统提出了一种多源异构数据和智能维护决策支持集成的新框架。该框架使用多代理系统来处理多源数据。每个代理都有其自己的任务,从将RDB(理性数据库)数据传输到RDF(资源描述框架)文件,然后通过Apache Jena API和D2RQ将本地RDF融合到全局RDF。此外,通过将粗糙集与欧氏距离相结合,构建了基于CBR(基于案例的推理)的用于故障诊断的智能维护决策支持。武广线上运营的CTCS-300T的VOBE(车载设备)的维护数据已经验证了所提出框架的正确性和有效性。

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